RNA flow

Code to accompany publication:
Ietswaart, R., Smalec, B.M., Xu, A., et al, (2024).
Genome-wide quantification of RNA flow across subcellular compartments reveals determinants of the mammalian transcript life cycle.
Mol Cell, 84
https://doi.org/10.1016/j.molcel.2024.06.008

01_subcell_timelapse_seq

Trim reads with Cutadapt

cutadapt.sh

STAR alignment

make_STAR_dirs.sh
run_align_human_ii.sh
which calls: align_human.sh

GRAND-SLAM (with default parameters):

bamToCIT_human_ii.sh
run_grandslam_human_ii_12combined.sh

Pc estimation

submit_process_n_k_turnover_WT_2023_h.sh
which calls:
process_n_k_turnover_WT_2023_h.sh
which calls:
top1000genes_turnover.R
modifyBed.R
MismatchScripts_batchSubmission/sortReads_byName_noSingles.R
bottom500genes_turnover.R

submit_parallel_findMM_h_i_rerun1.sh
which calls: findMismatches_complete_23_11_14_RI_variableGenome.R

prerun_MM_per_fragment_h_i.sh
which calls: sortReads_byName_23_11_19_RI.R

submit_run_MM_per_fragment_[m|h]_[i|ii|iii|iv].sh
which calls: MM_per_fragment_23-11-19_RI_batchSubmit.R

5. In the folders MM_temp_turnover
   run_shorten_fragments.sh

6. Generate the T>C mismatch frequency matrices.
   run_MM_freq.sh
   which calls:
   MM_[rep][frac].R
   MM[rep]_[frac]_slow.R

7. Estimate the pc using the binomial mixture model
   TCconversion_from_background_20231125_K562.sh
   which calls: TCconversion_from_background_20231125_K562.py

Rerun GRAND-SLAM with pc / pe estimates from binomial mixture model for top and bottom.

Copy the GS_run1 folder to new folders top and bottom. Remove the previous GS output files: [sample].tsv and [sample].ext.tsv in top/bottom folders. Replace the pc values with our respective top/bottom estimates into *.rates.tsv file in the rows single_new and double_new.
run_grandslam.sh

Merge GS top and bottom results (used for visualizations in MS)
GS20231201_MAP_CIs_from_topbottom_K562.sh
which calls: GS20231201_MAP_CIs_from_topbottom.py

02_kinetic_modeling

0. Generate a list of genes with GS data to analyze
   Timescale_Bayes_20231201_prerun.sh
   which calls: Timescale_Bayes_20231201_prerun.py

1. Batch run i
   Timescale_Bayes_20240119_K562_i.sh
   which calls: Timescale_Bayes_20240119.py

2. Batch run ii
   Timescale_Bayes_20240119_K562_ii.sh
   which calls:
   Timescale_Bayes_20240119_rerun.py
   Timescale_Bayes_20240119_rerun_no_nucdeg.py

3.0. Merge batch rate files
Timescale_Bayes_20240119_merge.sh
which calls: Timescale_Bayes_20240191_merge.py

3.1. Identify the genes that need a rerun for nucdeg rates
Timescale_Bayes_20240120_iii_prerun.sh
which calls: Timescale_Bayes_20240120_iii_prerun.py

3.2 Run iii for nucdeg rates
Timescale_Bayes_20240120_K562_iii.sh
which calls: Timescale_Bayes_20240120_nucdeg.py

4. Merge missing nucdeg rates into rate file
   Timescale_Bayes_20240120_merge_nucdeg.sh
   which calls: Timescale_Bayes_20240120_merge_nucdeg.py

Bayes Factor calculations

Four compartment Bayes factor calculation
Bayes_factor4_20231213_K562_i.sh
which calls: Bayes_factor4_20231213.py

Bayes_factor4_20231213_K562_ii.sh
which calls: Bayes_factor4_20231213_rerun.py

Bayes_factor4_20231213_iii_prerun.sh
which calls: Bayes_factor4_20231213_iii_prerun.py

Bayes_factor4_20231213_K562_iii.sh
which calls: Bayes_factor4_20231213_iii_prerun.py

Bayes_factor4_20231213_iv_prerun.sh
which calls: Bayes_factor4_20231213_iv_prerun.py

Bayes_factor4_20231213_K562_iv.sh
which calls: Bayes_factor4_20231213_rerun.py

Merge BF4 batches:
Bayes_factor4_20231213_merge.sh
which calls: Bayes_factor4_20231213_merge.py

Three compartment Bayes factor calculation
Bayes_factor3_20240110_K562_i.sh
which calls: Bayes_factor3_20240110.py

Bayes_factor3_20240110_K562_ii.sh
which calls: Bayes_factor3_20240110_rerun.py

Bayes_factor3_20240110_iii_prerun.sh
which calls: Bayes_factor3_20240110_iii_prerun.py

Bayes_factor3_20240110_K562_iii.sh
which calls: Bayes_factor3_20240110_rerun.py

Merge BF3 batches:
Bayes_factor3_20240110_merge.sh
which calls: Bayes_factor3_20240110_merge.py

Merge BF3 and BF4 results:
Bayes_factor4_20240112_merge_with_BF3.sh
which calls: Bayes_factor4_20240112_merge_with_BF3.py

03_nuclear_wash_subcell_rna_seq

Convert raw Illumina seq output (.bcl) to fastq
bcl2fastq_20230912.sh

fastQC (optional)
NucWash_fastqc_20230920.sh

Hardclip Illumina adapter sequences
NucWash_cutadapt_20231002.sh

Generate and concatenate human and yeast (spike-in) genome fasta and gtf / build STAR index
NucWash_STAR_index_20230915.sh

run STAR with default paired-end RNAseq parameters
NucWash_STAR_alignment_20231005.sh
which calls:
NucWash_CG20230908_parameters.in
NucWash_STAR_parameters.in

Get gene counts from alignments using featurecounts
NucWash_featureCounts_20231005.sh

Confirm that yeast spike in transcripts are in alignments (optional)
NucWash_inspect_bam_20231005.sh

Perform DE and PCA with spike in
NucWash_DEseq2_20240203.Rmd

Boxplots nuclear half lives vs Nuc Wash RNA levels
Nuc_cyto_ratios_NucWash_vs_rates_20240129.Rmd

04_subcell_nanostring

Erikstrings_fit_20220328.ipynb

05_gi_map

Alignment:
screen_processing_scripts_python3.sh

Analysis:
AXSNF03_analysis_cleaned.Rmd

06_ribosome_profiling

Alignment:
ribosome-profiling-preprocess-alignment_all_scripts.sh

Analysis:
AXSNF03_ribosome-profiling-analysis-cleaned.Rmd

07_DDX3X_subcell_rna_seq

Alignment:
fractionation_alignment_all_scripts.sh

Analysis:
AXSNF10-analysis-cleaned.Rmd

08_subcell_nanopore_seq

RNA_flow_alignment_directRNA_ONT.sh

09_subcell_timelapse_isoform

Script to generate a modified gtf for use with GRAND-SLAM:
GS20240122_Get_gene_level_gtf.sh

Script to generate a GRAND-SLAM index (.oml) file
GS20240122_Get_gedi_oml.sh

Scripts to filter all KDii samples and run GRAND-SLAM
GS20240122_Get_bed.sh
GS20240122_KDii_process_input_files.sh
GS20240122_KDii_extract_reads.sh
GS20240122_KDii_extract_reads_ii.sh
GS20240122_Get_bamlist.sh
GS20240122_KDii_run_GS.sh
GS20240122_MAP_CIs_from_topbottom_KD_ii.sh

Scripts to visualize results
GS20240122_KDii_visualization.R

Scripts for differential expression
GS20240122_featureCounts.sh
GS20240122_DEseq2.Rmd

Retained introns GRAND-SLAM control runs
GS20240122_Get_retained_intron_gtf.sh
GS20240122_Get_RI_gedi_oml.sh

scr pc parameter sweep control runs
GS20240305_Get_pc_files_folders.sh
GS20240305_KDii_run_GS.sh
Comparison_GS_KDii_20240305.ipynb

Final run for MS
GS20240309_Get_pc_files_folders.sh
GS20240309_KDii_run_GS.sh

10_lasso

First round of feature selection using individual feature classes with lasso regression
ML_20240122_subcell_feat_select1.sh
which calls: ML_20240122_subcell_feat_select1.py

Second round feature selection using the union of features selected in round 1
ML_20240122_subcell_feat_select2.sh
which calls: ML_20240122_subcell_feat_select2.py

Optimal hyperparameter identification, visualization and final file output
ML_20240122_subcell_analysis.ipynb